Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 16, issue 3
Articles | Volume 16, issue 3
https://doi.org/10.5194/gmd-16-1039-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-1039-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 3
Development and technical paper
 | 
09 Feb 2023
Development and technical paper |  | 09 Feb 2023

Bayesian transdimensional inverse reconstruction of the Fukushima Daiichi caesium 137 release

Joffrey Dumont Le Brazidec, Marc Bocquet, Olivier Saunier, and Yelva Roustan

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Latest update: 23 Nov 2024
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Short summary
When radionuclides are released into the atmosphere, the assessment of the consequences depends on the evaluation of the magnitude and temporal evolution of the release, which can be highly variable as in the case of Fukushima Daiichi. Here, we propose Bayesian inverse modelling methods and the reversible-jump Markov chain Monte Carlo technique, which allows one to evaluate the temporal variability of the release and to integrate different types of information in the source reconstruction.
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